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For NGS sequencing technology, the "deeper" you sequence given fragments, the more certain you are of what is being sequenced. This sounds like a simple application of Bayes's Rule.

What is the normal approach in the field to quantify one's level of certainty in NGS sequencing with Bayesian methods? There is also a statistical question here in terms of how one aligns reads, etc.

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  • $\begingroup$ This is a very broad question. There are possibly a thousand ways by which someone can apply bayesian inference to NGS data. $\endgroup$
    – WYSIWYG
    Jun 22 '16 at 4:56
  • $\begingroup$ @WYSIWYG I'm happy to delete the question. Could you refer me to techniques used now? $\endgroup$
    – ShanZhengYang
    Jun 22 '16 at 15:24
  • $\begingroup$ You can have a look at some of the RNAseq quanitification methods. There, one of the problem is to find out where exactly does a read come from (when there are many homologous regions). Bayesian methods are applied to infer the location of the read given its counts. From this the overall gene expression is estimated. $\endgroup$
    – WYSIWYG
    Jun 22 '16 at 15:29
  • $\begingroup$ @WYSIWYG Sorry to be lazy, but the names of these methods? $\endgroup$
    – ShanZhengYang
    Jun 22 '16 at 20:41
  • $\begingroup$ I have a reasonable level of familiarity with Bayesian methods, but not so much with NGS. If you can explain the question better I might be able to add something here. $\endgroup$
    – arboviral
    Apr 16 '18 at 15:37

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